zdifference_continuous: z-difference for continuous variables.

In weightedZdiff: Calculation of z-Differences

Description

The function calculates the continuous weighted z-Difference for a binary reference variable (ref) and a continuous variable (x)

Usage

zdifference_continuous(x, ref, w=NULL, na.rm = TRUE, r = 2)

Arguments

x	The continuous variable for which the weighted z-Difference should be calculated.
ref	The binary reference variable as a vector.
w	The weights to calculate the weighted continuous z-Difference
na.rm	Should NAs be removed or not. If NAs exists in dataset and na.rm=FALSE then an error will occure.
r	digits to round the returned value, default is 2

Value

The function returns the calculated z-Difference as a numeric value.

Author(s)

Tim Filla

References

For standard z-difference (unweighted) https://pubmed.ncbi.nlm.nih.gov/23972521/

Examples

#generate the data. The weights are taken from uniform distribution and the
#values of x are normal distributed with mean 45 and variance 9. The reference variable
#is chose from a bernoulli distribution with success rate 0.8.
ref<-sample(0:1,1000,replace=TRUE,prob=c(0.2,0.8))
erg<-unlist(lapply(1:1000,function(z){
  w<-runif(1000)
  x<-rnorm(1000,45,9)
  zdifference_continuous(x,ref,w)
}))
hist(erg,breaks=50,main="z-difference for continuous data")
plot(seq(0.005,0.97,0.01),quantile(erg,seq(0.005,0.97,0.01)),type="l",
lwd=3,xlab=c("quantile"),ylab=c("x-value"))
points(seq(0.005,0.97,0.01),qnorm(seq(0.005,0.97,0.01)),col="red",type="l",lwd=2,lty="dashed")

weightedZdiff documentation built on Aug. 18, 2020, 5:07 p.m.